What types of documents can a data capture solution process?

A data capture solution typically works with paper style file formats, such as PDFs and scanned images, converting inbound documents into a digital format suitable for business systems. It can also work in reverse, converting digital data into a format such as PDF for an outbound recipient, depending on what a business needs.

Why can OCR alone lead to errors in invoice processing?

OCR can recognise and read text within a document, but it cannot identify whether that data is actually correct. For example, it would process an invoice with the wrong pricing on it exactly as scanned, without flagging the error. This is why purely OCR based systems still often need manual review to catch mistakes.

How does AI improve on OCR for document processing?

AI adds a layer of pattern recognition and learning on top of basic text capture, so the system can flag documents that fail format or validation rules for review instead of processing them incorrectly. Once a correction is made, the system learns from it, so similarly formatted documents are processed correctly automatically in future, reducing the need for repeated manual checks.

What results has a data capture project delivered for a client in practice?

AG Barr, a Food and Beverage manufacturer that already had EDI in place, was still handling large volumes of inbound paper documents. Introducing a data capture solution across an initial group of ten priority customers freed up 572 man-hours of staff time a year that could be redirected to higher value work.

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How AI can upgrade a data capture solution

Smart businesses have a data capture solution to manage document processing across their business functions. However, with the development of AI technology they can benefit further from even more automated processes, here’s how…

Transalis4 August 2023

Conceptual image of paper planes one being help by a hand in the foreground, to represent business manual document processing and the need for a data capture solution for greater efficiency.

Key takeaways

Data capture technology converts paper documents, such as PDFs or scanned images, into a digital format for business systems, and can also work in reverse.
Data capture relying purely on OCR can read text but cannot identify or correct data errors, such as incorrect invoice pricing, so manual intervention is often still needed.
AI enhanced data capture learns from corrections, so it can automatically flag documents that fail format or validation checks and process similarly formatted documents correctly in future.
A workflow that accurately captures, separates, extracts, maps and validates inbound invoice data can convert it into any format needed to feed directly into a business's chosen system.
AG Barr, a Food and Beverage manufacturer using EDI, was processing volumes of inbound paper documents, so a new data capture solution freed up 572 man-hours a year.

What is the difference between traditional OCR based data capture and AI enhanced data capture?

Traditional data capture relies on Optical Character Recognition to read text within documents such as scanned images or PDFs, but it cannot identify or correct errors, so incorrect data like wrong pricing on an invoice can still be processed without review. AI enhanced data capture adds algorithms that learn from corrections, flag documents that fail format or validation checks, and automatically process similarly formatted documents correctly going forward, reducing the need for manual intervention.

Data capture for Accounts Payable

Increasingly struggling to manage the volume of inbound invoices in varying formats across your trading network? Inbound invoice automation removes the burden of manual processing to speed the payment cycle so your team can focus on more profitable tasks.

In this blog we’ll explore:

What a data capture solution is and what it does
How AI can enhance this technology for greater efficiency
Real-world examples from our client case studies

What is a data capture solution?

From a high-level perspective, a data capture solution works by capturing information from a document and converting it into a suitable format for various business systems.

These documents can be considered as “paper” file formats, such as PDFs or scanned images for example. There are a couple of different types of data capture solution. Depending on the business needs it can work in two ways:

Paper to digital: Where the data from a paper document (usually inbound) is converted into a suitable digital file format for business systems and ongoing processing
Digital to paper: Where the data from a digital file (usually outbound) is converted into a suitable format for the recipient (e.g. PDF)

How does data capture work?

Data capture typically relies on several technologies, the most common being OCR, or Optical Character Recognition. OCR data capture works by being able to recognise text within a file, such as images or PDFs.

The key benefits of data capture systems

Businesses that have a data capture system in place reap a number of benefits:

Eliminate human error: automating document processing removes the need for data rekeying and the associated time-consuming and costly human errors
Increase efficiency: again, automated processes remove the need for manual intervention, which significantly speeds up the processing time
Reduce costs: businesses with limited resources will not need to expand their teams purely for manual data management purposes, which cuts overhead costs
Digital audit trail: These systems typically provide an archive and full audit trail of processed documents

The limitations of a traditional data capture solution

As technology has advanced over recent years, data capture solutions that purely rely on OCR could be seen as outdated.

This is because the main downfall of OCR technology is that it is unable to identify and correct data errors. Using the Accounts Payable use case for data capture as an example, OCR would automate the processing of an invoice with incorrect pricing on it. In many cases, the use of pure OCR AP automation solutions still means a high likelihood of manual intervention.

So, the question is how businesses can have a fully automated data capture system in place? This is where Artificial Intelligence (AI) comes in…

How AI creates smart data capture

AI technology can be used to enhance these solutions for more intelligent document capture processing.

This AI technology can create smart data capture processing by handling specific tasks. It does this by relying on algorithms to identify patterns, learn and make decisions with minimal human intervention.

For example, our inbound invoice automation solution harnesses AI technology to process inbound invoices to approve for payment. It works by following a reliable workflow; accurately capturing, separating, extracting, mapping and validating the information that enables the full digital transformation of the invoice. These inbound documents can be converted into any compatible format for integration with and direct feed into the chosen business system.

To overcome the limitations of OCR, this AI-enhanced system can automatically flag any format and/or validation rejections that need to be reviewed and corrected. The best part is that these changes are then learned by the system to enable the automatic processing of similarly formatted invoices in future.

Transalis client case-studies

At Transalis, we have worked with many clients on digital transformation strategies and implemented solutions that use data capture technology.

One of these clients was the Food & Beverage manufacturer AG Barr. Whilst they had Electronic Data Interchange (EDI) in place across many trading connections, the organisation was still having to process large volumes of inbound paper documents, which was costing them greatly in resources. To tackle this, Transalis implemented a data capture solution that was able to perform paper to digital transformation.

AG Barr achieved an initial £15,000 annual saving on processes beginning with ten priority customers. The 5% improvement on processing also covered the initial investment spent on the project. Overall, AG Barr calculated that they saved 572 man-hours annually that can now be repurposed for higher-value operations.

The full case study has a detailed run-through of the business need, implementation process and the initial results, including commentary from AG Barr’s team. You can also read another client case study for Smeg, who came to us with a similar issue around the manual processing of incoming orders.

Whilst our Inbound invoice automation solution can handle incoming invoice documents, we also can provide paper to digital transformation for all kinds of different business documents. Our AI-enhanced data capture technology ensures businesses can efficiently process paper document formats, without disrupting existing workflows across their trading networks. Take a look at our eDI Freedom solution, which enables you to select the exact functionality and features you need, including inbound and/or outbound document transformation.

Frequently asked questions

What types of documents can a data capture solution process?: A data capture solution typically works with paper style file formats, such as PDFs and scanned images, converting inbound documents into a digital format suitable for business systems. It can also work in reverse, converting digital data into a format such as PDF for an outbound recipient, depending on what a business needs.
Why can OCR alone lead to errors in invoice processing?: OCR can recognise and read text within a document, but it cannot identify whether that data is actually correct. For example, it would process an invoice with the wrong pricing on it exactly as scanned, without flagging the error. This is why purely OCR based systems still often need manual review to catch mistakes.
How does AI improve on OCR for document processing?: AI adds a layer of pattern recognition and learning on top of basic text capture, so the system can flag documents that fail format or validation rules for review instead of processing them incorrectly. Once a correction is made, the system learns from it, so similarly formatted documents are processed correctly automatically in future, reducing the need for repeated manual checks.
What results has a data capture project delivered for a client in practice?: AG Barr, a Food and Beverage manufacturer that already had EDI in place, was still handling large volumes of inbound paper documents. Introducing a data capture solution across an initial group of ten priority customers freed up 572 man-hours of staff time a year that could be redirected to higher value work.

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